Nonparametric Bayesian Learning For Collaborative Robot Multimodal Introspection

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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

Author : Xuefeng Zhou
Publisher : Springer Nature
ISBN 13 : 9811562636
Total Pages : 149 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection by : Xuefeng Zhou

Download or read book Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection written by Xuefeng Zhou and published by Springer Nature. This book was released on 2020-01-01 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book focuses on robot introspection, which has a direct impact on physical human-robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.

Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

Author : Xuefeng Zhou
Publisher : Springer
ISBN 13 : 9789811562655
Total Pages : 137 pages
Book Rating : 4.5/5 (626 download)

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Book Synopsis Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection by : Xuefeng Zhou

Download or read book Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection written by Xuefeng Zhou and published by Springer. This book was released on 2020-09-18 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.

Bayesian Learning for Neural Networks

Author : Radford M. Neal
Publisher : Springer
ISBN 13 : 9780387947242
Total Pages : 204 pages
Book Rating : 4.9/5 (472 download)

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Book Synopsis Bayesian Learning for Neural Networks by : Radford M. Neal

Download or read book Bayesian Learning for Neural Networks written by Radford M. Neal and published by Springer. This book was released on 1996-08-09 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.

Bayesian Nonparametrics

Author : Nils Lid Hjort
Publisher : Cambridge University Press
ISBN 13 : 1139484605
Total Pages : 309 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Bayesian Nonparametrics by : Nils Lid Hjort

Download or read book Bayesian Nonparametrics written by Nils Lid Hjort and published by Cambridge University Press. This book was released on 2010-04-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount of data. Computational issues, though challenging, are no longer intractable. All that is needed is an entry point: this intelligent book is the perfect guide to what can seem a forbidding landscape. Tutorial chapters by Ghosal, Lijoi and Prünster, Teh and Jordan, and Dunson advance from theory, to basic models and hierarchical modeling, to applications and implementation, particularly in computer science and biostatistics. These are complemented by companion chapters by the editors and Griffin and Quintana, providing additional models, examining computational issues, identifying future growth areas, and giving links to related topics. This coherent text gives ready access both to underlying principles and to state-of-the-art practice. Specific examples are drawn from information retrieval, NLP, machine vision, computational biology, biostatistics, and bioinformatics.

Factor Graphs for Robot Perception

Author : Frank Dellaert
Publisher :
ISBN 13 : 9781680833263
Total Pages : 162 pages
Book Rating : 4.8/5 (332 download)

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Book Synopsis Factor Graphs for Robot Perception by : Frank Dellaert

Download or read book Factor Graphs for Robot Perception written by Frank Dellaert and published by . This book was released on 2017-08-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reviews the use of factor graphs for the modeling and solving of large-scale inference problems in robotics. Factor graphs are introduced as an economical representation within which to formulate the different inference problems, setting the stage for the subsequent sections on practical methods to solve them.

Encyclopedia of Information Science and Technology

Author : Mehdi Khosrow-Pour
Publisher : IGI Global Snippet
ISBN 13 : 9781605660264
Total Pages : 4292 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Encyclopedia of Information Science and Technology by : Mehdi Khosrow-Pour

Download or read book Encyclopedia of Information Science and Technology written by Mehdi Khosrow-Pour and published by IGI Global Snippet. This book was released on 2009 with total page 4292 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This set of books represents a detailed compendium of authoritative, research-based entries that define the contemporary state of knowledge on technology"--Provided by publisher.

Robot Learning from Human Demonstration

Author : Sonia Dechter
Publisher : Springer Nature
ISBN 13 : 3031015703
Total Pages : 109 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Robot Learning from Human Demonstration by : Sonia Dechter

Download or read book Robot Learning from Human Demonstration written by Sonia Dechter and published by Springer Nature. This book was released on 2022-06-01 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.

Human-Robot Interaction

Author : Céline Jost
Publisher : Springer Nature
ISBN 13 : 3030423077
Total Pages : 418 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Human-Robot Interaction by : Céline Jost

Download or read book Human-Robot Interaction written by Céline Jost and published by Springer Nature. This book was released on 2020-05-13 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers the first comprehensive yet critical overview of methods used to evaluate interaction between humans and social robots. It reviews commonly used evaluation methods, and shows that they are not always suitable for this purpose. Using representative case studies, the book identifies good and bad practices for evaluating human-robot interactions and proposes new standardized processes as well as recommendations, carefully developed on the basis of intensive discussions between specialists in various HRI-related disciplines, e.g. psychology, ethology, ergonomics, sociology, ethnography, robotics, and computer science. The book is the result of a close, long-standing collaboration between the editors and the invited contributors, including, but not limited to, their inspiring discussions at the workshop on Evaluation Methods Standardization for Human-Robot Interaction (EMSHRI), which have been organized yearly since 2015. By highlighting and weighing good and bad practices in evaluation design for HRI, the book will stimulate the scientific community to search for better solutions, take advantages of interdisciplinary collaborations, and encourage the development of new standards to accommodate the growing presence of robots in the day-to-day and social lives of human beings.

Probabilistic Robotics

Author : Sebastian Thrun
Publisher : MIT Press
ISBN 13 : 0262201623
Total Pages : 668 pages
Book Rating : 4.2/5 (622 download)

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Book Synopsis Probabilistic Robotics by : Sebastian Thrun

Download or read book Probabilistic Robotics written by Sebastian Thrun and published by MIT Press. This book was released on 2005-08-19 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the techniques and algorithms of the newest field in robotics. Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

Introduction to Information Retrieval

Author : Christopher D. Manning
Publisher : Cambridge University Press
ISBN 13 : 1139472100
Total Pages : pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Introduction to Information Retrieval by : Christopher D. Manning

Download or read book Introduction to Information Retrieval written by Christopher D. Manning and published by Cambridge University Press. This book was released on 2008-07-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Model Selection and Multimodel Inference

Author : Kenneth P. Burnham
Publisher : Springer Science & Business Media
ISBN 13 : 0387224564
Total Pages : 512 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Model Selection and Multimodel Inference by : Kenneth P. Burnham

Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2007-05-28 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

Reinforcement Learning, second edition

Author : Richard S. Sutton
Publisher : MIT Press
ISBN 13 : 0262352702
Total Pages : 549 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Reinforcement Learning, second edition by : Richard S. Sutton

Download or read book Reinforcement Learning, second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Data Intelligence and Cognitive Informatics

Author : I. Jeena Jacob
Publisher : Springer Nature
ISBN 13 : 981158530X
Total Pages : 916 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Data Intelligence and Cognitive Informatics by : I. Jeena Jacob

Download or read book Data Intelligence and Cognitive Informatics written by I. Jeena Jacob and published by Springer Nature. This book was released on 2021-01-08 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2020), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during 8–9 July 2020. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.

Grasping in Robotics

Author : Giuseppe Carbone
Publisher : Springer Science & Business Media
ISBN 13 : 1447146646
Total Pages : 464 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Grasping in Robotics by : Giuseppe Carbone

Download or read book Grasping in Robotics written by Giuseppe Carbone and published by Springer Science & Business Media. This book was released on 2012-11-15 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grasping in Robotics contains original contributions in the field of grasping in robotics with a broad multidisciplinary approach. This gives the possibility of addressing all the major issues related to robotized grasping, including milestones in grasping through the centuries, mechanical design issues, control issues, modelling achievements and issues, formulations and software for simulation purposes, sensors and vision integration, applications in industrial field and non-conventional applications (including service robotics and agriculture). The contributors to this book are experts in their own diverse and wide ranging fields. This multidisciplinary approach can help make Grasping in Robotics of interest to a very wide audience. In particular, it can be a useful reference book for researchers, students and users in the wide field of grasping in robotics from many different disciplines including mechanical design, hardware design, control design, user interfaces, modelling, simulation, sensors and humanoid robotics. It could even be adopted as a reference textbook in specific PhD courses.

ROS by Example

Author : R. Patrick Goebel
Publisher :
ISBN 13 :
Total Pages : 258 pages
Book Rating : 4.:/5 (927 download)

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Book Synopsis ROS by Example by : R. Patrick Goebel

Download or read book ROS by Example written by R. Patrick Goebel and published by . This book was released on 2015 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at new ROS users who want to go beyond the Beginner Tutorials and create some working ROS applications, either in simulation or on a real robot like the TurtleBot. The book provides step-by-step explanations of a number of ROS programming examples using code that can be downloaded from the accompanying ros-by-example repository.

Essentials of Metaheuristics (Second Edition)

Author : Sean Luke
Publisher :
ISBN 13 : 9781300549628
Total Pages : 242 pages
Book Rating : 4.5/5 (496 download)

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Book Synopsis Essentials of Metaheuristics (Second Edition) by : Sean Luke

Download or read book Essentials of Metaheuristics (Second Edition) written by Sean Luke and published by . This book was released on 2012-12-20 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interested in the Genetic Algorithm? Simulated Annealing? Ant Colony Optimization? Essentials of Metaheuristics covers these and other metaheuristics algorithms, and is intended for undergraduate students, programmers, and non-experts. The book covers a wide range of algorithms, representations, selection and modification operators, and related topics, and includes 71 figures and 135 algorithms great and small. Algorithms include: Gradient Ascent techniques, Hill-Climbing variants, Simulated Annealing, Tabu Search variants, Iterated Local Search, Evolution Strategies, the Genetic Algorithm, the Steady-State Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, Genetic Programming variants, One- and Two-Population Competitive Coevolution, N-Population Cooperative Coevolution, Implicit Fitness Sharing, Deterministic Crowding, NSGA-II, SPEA2, GRASP, Ant Colony Optimization variants, Guided Local Search, LEM, PBIL, UMDA, cGA, BOA, SAMUEL, ZCS, XCS, and XCSF.

Logistics 4.0

Author : Turan Paksoy
Publisher : CRC Press
ISBN 13 : 1000245101
Total Pages : 369 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Logistics 4.0 by : Turan Paksoy

Download or read book Logistics 4.0 written by Turan Paksoy and published by CRC Press. This book was released on 2020-12-17 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.